System and Method for Training Non-Parametric Machine Learning Model Instances in a Collaborative Manner

2. The method as claimed in claim 1, wherein the non-parametric ML model instances are one of a Decision-Tree, Random Forest, Bayesian model, K-Nearest Neighbors (KNN), and Support Vector Machines (SVM).

3. The method as claimed in claim 1, wherein the trainable parametric combinator is a parametric ML model selected from at least one of Logistic Regression, Linear Discriminant Analysis, Perceptron, Naive Bayes, and Neural Network.

4. The method as claimed in claim 1, wherein the non-parametric ML model instances are obfuscated by the first subset of the plurality of data processing nodes before sharing with the second subset of the plurality of data processing nodes.

5. The method as claimed in claim 4, wherein at least one non-parametric ML model instance is obfuscated using an Open Neural Network Exchange (ONNX) model.

6. The method of claim 1, wherein the inference process is initiated at the second subset of the plurality of data processing nodes.

8. The method of claim 1, wherein the trainable parametric combinator utilizes parameters from the plurality of non-parametric ML model instances in generating the set of composite models.

10. The method of claim 1, wherein the sharing between the first subset and the second subset comprises writing a blockchain transaction using a blockchain application programming interface (API).

12. The blockchain system as claimed in claim 11, wherein the non-parametric ML model instances are at least one of a Decision-Tree, Random Forest, Bayesian model, K-Nearest Neighbors (KNN), and Support Vector Machines (SVM).

13. The blockchain system as claimed in claim 11, wherein the trainable parametric combinator is a parametric ML model selected from at least one of Logistic Regression, Linear Discriminant Analysis, Perceptron, Naive Bayes, and Neural Network.

14. The blockchain system as claimed in claim 11, wherein the non-parametric ML model instances are obfuscated by the first subset of the plurality of data processing nodes before sharing with the second subset of the plurality of data processing nodes.

15. The blockchain system as claimed in claim 14, wherein at least one non-parametric ML model instance is obfuscated using an Open Neural Network Exchange (ONNX) model.

17. The non-transitory computer-readable storage medium in claim 16, wherein the non-parametric ML model instances are one of a Decision-Tree, Random Forest, Bayesian model, K-Nearest Neighbors (KNN), and Support Vector Machines (SVM).

18. The non-transitory computer-readable storage medium in claim 16, wherein the trainable parametric combinator is a parametric ML model selected from at least one of Logistic Regression, Linear Discriminant Analysis, Perceptron, Naive Bayes, and Neural Network.

19. The non-transitory computer-readable storage medium in claim 16, wherein the non-parametric ML model instances are obfuscated by the first subset of the plurality of data processing nodes before sharing with the second subset of the plurality of data processing nodes.

20. The non-transitory computer-readable storage medium in claim 19, wherein at least one non-parametric ML model instance is obfuscated using an Open Neural Network Exchange (ONNX) model.